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Deploying PostGIS in the Cloud

Duration: 3 Days

Course Background

This 3 day workshop is concerned with scaling GIS data , transforming the data between NoSQL and SQL databases e.g. between PostgreSQL and HBase or between PostgreSQL and Cassandra or between PostgreSQL and MongoDB, and also performing distributed computations retrieving data from a variety of SQL and NoSQL sources for data analysis and data mining purposes. The whole field is very much in a state of rapid evolution and change and the intention is to provide attendees with a reasonably up to date overview of open source technologies, problems and solutions focuses around core PostGIS data stores.

Course Prerequisites and Target Audience

Attendees are assumed to have a reasonable amount of knowledge and experience with PostGIS and cloud computing and an interest in exploring possible approaches involved in scaling GIS to very BigData GIS systems.

Course Outline

    • GIS = maps + analysis
    • Maps = Graphics + Images + Geometric Information + Factual information
    • Storing GIS data in a Spatial Database Management System (SDBMS) - PostGIS
    • Partitioning an SDBMS and deploying particioned segments in the Cloud
    • Parallelising spatial joins across an SDBMS cluster with MapReduce
    • Storing GIS data in a NoSQL database
    • Storing and structuring GIS data using HBase and Hive
    • Moving and sharing data between PostGIS and HBase
    • Deploying PostgreSQL and PostGIS in the cloud
      • Deploying postgreSQL and PostGIS on the Amazon cloud using RDS (Amazon Relational Data Service)
      • Deploying PostgreSQL and PostGIS on Red Hat OpenShift
      • Deploying PostgreSQL and PostGIS on OpenStack
    • Hadoop, HBase and Hive
      • Hadoop-GIS - High Performance Spatial Data Warehousing over Map-Reduce
      • Saving shapefiles in Hadoop HDFS
      • Spatial indexing limitations in HBase
      • Moving data between PostGIS and HBase
    • MongoDB
      • Overview of MongoDB
      • Using MongoDB for GIS
      • Issues with MongoDB spatial indexing
      • Moving data between PostGIS and MongoDB
    • Cassandra
      • Overview of Cassandra
      • Using Cassandra for GIS
      • Issues with Cssandra and spatial indexing
      • Moving data between PostGIS and Cassandra
    • Data Fusion
      • Data Fusion - Integration of GIS and Remote Sensing
      • Data Fusion Centers, GIS and Cloud Computing - Possibilities and Potential
    • Cloud clusters with mixed data stores e.g.
      • Cassandra database for columnar data structures
      • PostgreSQL for relational data structures
      • Hadoop distributed file system for large unstructured and noisy data